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teaching:mfe:ia [2019/02/18 12:15] bersini |
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| * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | ||
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| ===== Développer un programme informatique permettant une analyse statistique en vue de l'évaluation d'un module psychothérapeutique. ===== | ===== Développer un programme informatique permettant une analyse statistique en vue de l'évaluation d'un module psychothérapeutique. ===== | ||
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| * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | ||
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| ===== Développer des solutions de text mining pour la société Procter & Gamble ===== | ===== Développer des solutions de text mining pour la société Procter & Gamble ===== | ||
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| * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | ||
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| + | ===== Le data mining en tant qu’outil d’aide à la gestion active d’actifs cotés ===== | ||
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| + | L’idée de ce mémoire serait d’avoir un travail en plusieurs parties dont notamment : | ||
| + | • une partie théorique qui reprendrait les fondamentaux du data mining, | ||
| + | • un screening, une présentation et comparaison des outils existants utilisés dans le cadre de la gestion d’actifs cotés, | ||
| + | • une partie pratique destinée à construire un data set et à le modéliser. | ||
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| + | * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | ||
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| + | ===== Speed-up Techniques for Shortest Path Problems ===== | ||
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| + | The shortest path problem is one of the most important in combinatorial optimization and has multiple real-world applications. | ||
| + | The well-known Dijkstra algorithm solves the shortest path problem in any weighted graph with non-negative weights. However, with the recent increase of the amount of data, we feel the need to drastically increase the execution time of the algorithm. | ||
| + | In the latest years, we observe the emergence of a lot of new speed-up techniques; among them there are: heuristic search, bidirectional search, landmarks, reaches, short-cuts and contractions. The efficiency of these techniques heavily depends on the topology of the graph. Moreover, graphs with more complex structures (as user-adapted graphs) do not support some of these techniques, at least as they are currently presented. | ||
| + | From these observations, several questions arise, among them we propose: | ||
| + | Which optimization methods are the most efficient depending on the graph topology? | ||
| + | How can we adapt these techniques to more complex graph structures? | ||
| + | Other research questions in this topic can be proposed and discussed. | ||
| + | These questions can be studied from both theoretical and empirical approach. | ||
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| + | * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | ||
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| + | ===== Développer des solutions de data mining pour la société BMW Group Belux ===== | ||
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| + | Ce mémoire se fera en collaboration avec des responsables marketing et techniques de cette société. | ||
| + | Les sujets pourraient couvrir tout ce qui concerne les data, tant les data dites de campagne, communication, que celles liées à la production ou aux véhicules connectés. | ||
| + | * Contact : [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | ||
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| ===== Transposition en logique floue des réseaux de neurones récurrents de type GRU ===== | ===== Transposition en logique floue des réseaux de neurones récurrents de type GRU ===== | ||
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| * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
| * [[https://www.ee-ip.org/|Jürgen Ritzek (EE-IP)]] | * [[https://www.ee-ip.org/|Jürgen Ritzek (EE-IP)]] | ||
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| - | ===== Software framework for ant colony optimization ===== | ||
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| - | Ants have inspired a number of computational techniques and among the most successful is ant colony optimization (ACO). ACO is an optimization technique that can be applied to tackle a wide variety of computational problems that arise in computer science, telecommunications, and engineering. While ACO has a very wide applicability, the development times for effective ACO algorithms can be relatively high. This is due to the fact that each time a new problem is to be tackled by an ACO algorithm, a researcher needs to implement the algorithms almost from scratch. | ||
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| - | The goal of the project is to provide a software framework to support the application and the implementation of ACO algorithms to new problems. The software framework will offer all the standard procedures that are used in ACO algorithms and will allow for the rapid prototyping of ACO algorithms. | ||
| - | The application of this software framework will be tested on a number of optimization problems. | ||
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| - | Required skills: The candidate should be well acquainted with programming in object oriented languages. | ||
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| - | * Contacts : | ||
| - | * [[http://iridia.ulb.ac.be/~mdorigo|Marco Dorigo (IRIDIA)]] | ||
| - | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||